Estimation of stochastic volatility and option prices

Abstract

This study suggests a method to estimate a stochastic volatility model incorporating both information on high/low prices and the leverage effect. The likelihood-based inference of Markov Chain Monte Carlo is conducted to estimate parameters and volatility. Simulation reveals that our method improves estimation and pricing options. We also find that the information on high/low prices is more likely to contribute to the improvement than the leverage effect.